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Jupyter notebook script to demonstrate the use of the machine learning databases and analysis for Journal of Geophysical Research: Space Physics manuscript: "New capabilities for prediction of high-latitude ionospheric scintillation: A novel approach with machine learning."

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posted on 2018-10-16, 14:56 authored by Ryan McGranaghanRyan McGranaghan, Anthony Mannucci, Chris MattmannChris Mattmann, Brian Wilson, Richard Chadwick
This Jupyter notebook script provides processing details to support the analysis and results of the Journal of Geophysical Research: Space Physics manuscript: "New capabilities for prediction of high-latitude ionospheric scintillation: A novel approach with machine learning."

It uses the two machine learning database data sets also provided in this FigShare project.

Funding

This research was supported by the NASA Living With a Star Jack Eddy Postdoctoral Fellowship Program, administered by the University Corporation for Atmospheric Research and coordinated through the Cooperative Programs for the Advancement of Earth System Science (CPAESS). Portions of this research were carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.

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